The poor outside the lamplight: on the prevalence of poverty among population groups not included in household surveys

Poverty rate calculations are often based on household surveys that exclude some of the groups most vulnerable to poverty such as the homeless. This paper documents the nature of the excluded groups and the quantitative importance of their omission for the Czech Republic. Our study combines European Union Statistics on Income and Living Conditions data for 2011 with information from the 2011 Population Census. Our preferred estimate indicates an increase in the poverty rate by almost one percentage point. The paper contributes to accurately identifying the most vulnerable members of the society, which is essential for setting effective social policies.     

Stock market volatility forecasting: Do we need high-frequency data?

The general consensus in the volatility forecasting literature is that high-frequency volatility models outperform low-frequency volatility models. However, such a conclusion is reached when low-frequency volatility models are estimated from daily returns. Instead, we study this question considering daily, low-frequency volatility estimators based on open, high, low, and close daily prices. Our data sample consists of 18 stock market indices. We find that high-frequency volatility models tend to outperform low-frequency volatility models only for short-term forecasts. As the forecast horizon increases (up to one month), the difference in forecast accuracy becomes statistically indistinguishable for most market indices. To evaluate the practical implications of our results, we study a simple asset allocation problem. The results reveal that asset allocation based on high-frequency volatility model forecasts does not outperform asset allocation based on low-frequency volatility model forecasts.     

Using artificial neural network and multivariate analysis techniques to evaluate road operating conditions

Regional paved roads are low volume roads with a prevalence of heavy traffic. In the world, these roads concern about 80% of the total road network; however, the traffic that affects these roads is about 20%. Since regional roads are characterized by weak demand, budget for their management/maintenance is very low. This produces considerable difficulties in the choice of strategies for maintenance planning and scheduling. For this reason, the recurring topics of research in this field deal with typical roads issues and aim to develop low cost tools and methods. The study proposes a decision support system to evaluate regional paved roads operating condition in relation to the hydrogeological situation. In particular, the system allows to evaluate in a quick and easy manner, the operating conditions of the road, through low-cost tools (i.e. using low economic resources). This is very useful in the case of LVRs because administrations for these roads have a limited budget. The procedure is developed on a regional paved roads network based on more than 80 roads located in Southern Italy. Data is collected by direct surveys in the field and is integrated with cartography and information available in road agency records. From data analysis, obtained using two different techniques, an easy and quick use procedure is made. In particular, Model 1 is built through multivariate analysis and Model 2 using the artificial neural network (ANN) technique. The results show the validity of the two models in Regional paved roads operating conditions estimation in relation to hydrogeological situations of sites. Both models show good reliability. In particular, the first model (Model 1) is characterized by a high level of significance (p < 0.01) and by a coefficient of determination equal to 0.82. Comparative tests between the second model (Model 2) on which standard tests cannot be performed for obvious reasons, and the first model (Model 1). The results show that the ANN model (model 2), characterized by lower residual, simulates more accurately than the second (Model 1).     

The risks connected with accidents on highways and railways

Quality & Quantity - Safety in an integral sense is a comprehensive tool by which the humans ensure the level of their security and the sustainable development of them and of other basic public...     

Reliable Estimates of Sovereign Rating

International Advances in Economic Research -     

Dreaming of the West: The power of the brand in Soviet Lithuania, 1960s–1980s

Abstract

The article reveals the interest in foreign trademarks observed in Lithuanian society from the 1960s through the 1980s, when the demand for brand names spread after Western culture reached the Soviet Union. The consumption of Western cultural products, or imitations thereof, became one of the key symbolic expressions of freedom in Soviet society. In Lithuania, the most popular clothes were those bearing fake trademarks, even though Soviet authorities attempted to prevent the desire for and the wearing of these garments through the use of ideological tools.     

Moral Pragmatism as a Bridge Between Duty,Utility, and Virtue in Managers’ Ethical Decision-Making

Journal of Business Ethics - The decline of empirical research on ethical decision-making based on ethical theories might imply a tacit consensus has been reached. However, the exclusion of virtue...     

REPORTING GUIDELINES FOR META-ANALYSIS IN ECONOMICS

Meta-analysis has become the conventional approach to synthesizing the results of empirical economics research. To further improve the transparency and replicability of the reported results and to raise the quality of meta-analyses, the Meta-Analysis of Economics Research Network has updated the reporting guidelines that were published by this Journal in 2013. Future meta-analyses in economics will be expected to follow these updated guidelines or give valid reasons why a meta-analysis should deviate from them.